This project presents the design and development of a non-invasive multi-parameter health monitoring system capable of estimating blood glucose, hemoglobin concentration, and hydration levels in real time using Arduino-based optical and spectroscopy sensor technologies. The system integrates various non-invasive sensing modules including a Near Infrared (NIR) module for glucose estimation, IR and Red LEDs with photodiodes for hemoglobin measurement, and a spectroscopy module covering wavelengths between 940–1450 nm for hydration monitoring. The working principle is based on optical absorption and reflectance, where transmitted or reflected light through fingertip tissue is analyzed to extract physiological information. estimating blood glucose levels based on the absorption and reflection of light through fingertip tissue. Using Beer–Lambert law, Arduino processes sensor outputs and estimates glucose and hemoglobin concentrations through calibration routines and regression. Hydration status is determined by analyzing light absorption variations sensitive to water content. The system displays real-time readings on an LCD screen, triggers buzzer alerts for abnormal values, and utilizes the ESP8266 Wi-Fi module for wireless data transmission to ThingSpeak for remote health tracking and data logging. Powered by an adapter-based supply, this prototype demonstrates a low-cost, portable, and user-friendly non-invasive health monitoring solution, suitable for personal healthcare and preventive medical applications.    

Objectives:

• To develop a non-invasive multi-parameter health monitoring system capable of measuring blood glucose, hemoglobin concentration, and hydration levels using optical and spectroscopy-based sensor technologies.
• To utilize Near Infrared (NIR) sensing techniques for estimating blood glucose levels based on the absorption and reflection of light through fingertip tissue.
• To measure hemoglobin concentration non-invasively using IR and Red LEDs in conjunction with optical detectors such as photodiodes, applying the Beer–Lambert law for absorption analysis.
• To monitor hydration status in real time using a spectroscopy module with multiple wavelength LEDs to detect water absorption characteristics in skin tissue.
• To perform calibration and data modeling using regression technique for accurate prediction of glucose, hemoglobin, and hydration levels.
• To integrate Arduino UNO as the central processing and control unit for acquiring, processing, and displaying sensor data on LCD display.
• To provide wireless data logging and cloud integration through the ESP8266 Wi-Fi module for remote monitoring using the ThingSpeak platform.
• To generate real-time alerts via a Buzzer when abnormal physiological parameters are detected.

    The major building blocks of this project are:

• Power supply.
• Arduino UNO.
• NIR module.
• IR and RED LEDs.
• Spectroscopy module.
• LCD display.
• Buzzer.
• ESP8266 WI-FI module.

  Software’s used:

• ARDUINO IDE.
• Embedded C language.

 

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